CN111368261A - A quantitative and qualitative description method for impervious surface index based on atmospheric correction - Google Patents
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Abstract
本发明请求保护一种基于大气校正对不透水面指数的定量定性描述方法，该方法包括：通过现有的方法针对研究区域的Landsat8遥感影像进行数据预处理，本文研究了基于不同辐射校正水平(辐射定标和FLASSH大气校正)的遥感数据，以重庆主城为研究区域，利用Landsat‑8影像的灰度值(Digital Number,DN)、表观(Top of the Atmospher,TOA)反射率与地表(Surface)反射率提取不同类型的建筑指数，反演了灰度值、辐射定标、大气校正三个不同处理阶段的NDBI、IBI、UI、BUAI不透水面指数变化特征、分布范围、相关系数和提取精度进行了详细的对比分析，评价了大气校正对反演的建筑指数性能差异的影响。本方法可为遥感影响不透水面信息的提取，提供一定的研究意义和应用价值。
The present invention claims to protect a quantitative and qualitative description method for the impervious surface index based on atmospheric correction. Radiometric calibration and FLASSH atmospheric correction) remote sensing data, taking the main city of Chongqing as the study area, using the gray value (Digital Number, DN), apparent (Top of the Atmospher, TOA) reflectance and surface reflectance of Landsat‑8 images (Surface) reflectivity extracts different types of building indices, and inverts the variation characteristics, distribution range, and correlation coefficients of NDBI, IBI, UI, and BUAI impervious surface indices in three different processing stages: gray value, radiometric calibration, and atmospheric correction. A detailed comparative analysis was carried out with the extraction accuracy, and the effect of atmospheric correction on the performance difference of the retrieved building index was evaluated. This method can provide a certain research significance and application value for the extraction of remote sensing impact information on impervious surfaces.
Description
技术领域technical field
本发明属于城市不透水面信息的领域。具体反演了灰度值、辐射定标、大气校正三个不同处理阶段的4种不透水面指数，进一步定量分析大气校正对不透水面指数性能差异影响的方法。The invention belongs to the field of urban impervious surface information. Specifically, four kinds of impervious surface indices in three different processing stages of gray value, radiometric calibration, and atmospheric correction were inverted, and the method of the influence of atmospheric correction on the performance difference of impervious surface indices was further analyzed quantitatively.
背景技术Background technique
不透水面指数是遥感领域中提取城市不透水面分布、反应城市的动态扩展的遥感技术，国内外学者进行了大量的研究。但是，遥感影像通常会受到传感器自身以及大气、气溶胶等多因素的干扰，所以经过大气校正来提取城市不透水面指数是很有必要的。Impervious surface index is a remote sensing technology in the field of remote sensing to extract the distribution of urban impervious surface and reflect the dynamic expansion of the city. Scholars at home and abroad have conducted a lot of research. However, remote sensing images are usually interfered by the sensor itself, the atmosphere, aerosols and other factors, so it is necessary to extract the urban impervious surface index through atmospheric correction.
遥感数据反演不透水面指数大多是用DN值来进行表示，DN值是遥感影像像元亮度值，记录地物的灰度值，无单位。TOA反射率是地面反射辐射量与入射辐射量之比，Surface反射率是指大气层顶的反射率,简称表观反射率。参与城市不透水面指数计算的反射率,既可以是DN值、TOA反射率,也可以是大气校正后的Surface反射率。有大量的研究表明，基于遥感影像的灰度值、表观反射率或地表反射率均可以计算植被指数，但是根据辐射定标与大气校正后的地表辐射亮度值或反射率计算出的植被指数最为准确。目前有学者对不同辐射正水平下植被指数特征对比分析，采用定量遥感和回归分析方法从空间和时间两个方面对不同辐射水平下提取的NDVI变化特征进行了详细的对比分析，定量评价了大气对于提取的植被指数的影响。还有学者对大气校正开展与否和NDVI阈值选取对绿潮面积遥感提取精度的影响进行了研究。The impervious surface index of remote sensing data inversion is mostly expressed by the DN value. The DN value is the brightness value of the remote sensing image pixel, and the gray value of the recorded ground object is unitless. TOA reflectance is the ratio of ground reflected radiation to incident radiation, and Surface reflectance refers to the reflectance of the top of the atmosphere, referred to as apparent reflectance. The reflectivity involved in the calculation of the urban impervious surface index can be either the DN value, the TOA reflectivity, or the surface reflectivity after atmospheric correction. A large number of studies have shown that the vegetation index can be calculated based on the gray value, apparent reflectance or surface reflectance of remote sensing images, but the vegetation index is calculated based on the surface radiance value or reflectance after radiometric calibration and atmospheric correction. most accurate. At present, some scholars have compared and analyzed the characteristics of vegetation index under different positive radiation levels, using quantitative remote sensing and regression analysis methods to compare and analyze the variation characteristics of NDVI extracted under different radiation levels in space and time in detail, and quantitatively evaluated the atmospheric Effects on the extracted vegetation index. Other scholars have studied the influence of atmospheric correction and NDVI threshold selection on the extraction accuracy of green tide area by remote sensing.
目前大多数学者对于城市不透水面指数的提取，为了方便就直接使用原始影像的DN值反演，没有去考虑大气校正是否有助于提高不透水面指数性能。在DN值、TOA反射率、Surface反射率下反演的不透水面指数性能综合分析比较的研究较少，同时大气校正对提取城市不透水面指数的的影响缺乏应有的重视，因此对不同处理方法得出的结果做进一步对比研究是有必要的。本文利用Landsat-8遥感数据，对比分析在灰度值(DN),表观(TOA)反射率与地表(Surface)反射率反演的几种具有代表性的不透水面指数的分布范围、变化特征、相关系数和提取精度，探讨了大气校正对建筑指数性能差异的影响，为今后的Landsat-8数据提取建筑指数的研究提供借鉴和参考。At present, most scholars directly use the DN value of the original image for the extraction of the urban impervious surface index for convenience, and do not consider whether atmospheric correction can help improve the performance of the impervious surface index. There are few studies on the comprehensive analysis and comparison of the performance of the impervious surface index retrieved under the DN value, TOA reflectivity, and Surface reflectivity. At the same time, the influence of atmospheric correction on the extraction of the urban impervious surface index lacks due attention. It is necessary to conduct further comparative study on the results obtained by the treatment method. This paper uses Landsat-8 remote sensing data to compare and analyze the distribution range and variation of several representative impervious surface indices in the gray value (DN), apparent (TOA) reflectance and surface (Surface) reflectance inversion. The characteristics, correlation coefficients and extraction accuracy are discussed, and the influence of atmospheric correction on the performance difference of building index is discussed, which can provide reference and reference for future research on the extraction of building index from Landsat-8 data.
发明内容SUMMARY OF THE INVENTION
本发明旨在解决以上现有技术的问题。提出了一种基于大气校正对不透水面指数的定量定性描述方法。本发明的技术方案如下：The present invention aims to solve the above problems of the prior art. A quantitative and qualitative description method for impervious surface index based on atmospheric correction is proposed. The technical scheme of the present invention is as follows:
一种基于大气校正对不透水面指数的定量定性描述方法，其包括以下步骤：A quantitative and qualitative description method for impervious surface index based on atmospheric correction, which includes the following steps:
1)、获取研究区域的Landsat8遥感影像；1), obtain the Landsat8 remote sensing image of the study area;
2)、对原始遥感影像数据进行预处理，包括大气校正、辐射定标以及几何校正；2) Preprocessing the original remote sensing image data, including atmospheric correction, radiometric calibration and geometric correction;
3)、获取辐射定标和FLASSH大气校正的遥感数据，经过辐射定标、大气校正后，得到Landsat-8影像的灰度值DN、表观TOA反射率与地表Surface反射率；3), obtain the remote sensing data of radiometric calibration and FLASSH atmospheric correction, after radiometric calibration and atmospheric correction, obtain the gray value DN, apparent TOA reflectivity and surface reflectivity of the Landsat-8 image;
4)、反演灰度值、辐射定标、大气校正三个不同处理阶段的4种不透水面指数；4) Four kinds of impervious surface indices in three different processing stages: gray value inversion, radiometric calibration, and atmospheric correction;
5)、采用数理统计方法得到三个不同处理阶段的4种不透水面指数变化特征、分布范围；5), using mathematical statistics method to obtain the variation characteristics and distribution range of 4 kinds of impervious surface indices in three different treatment stages;
6)、采用数理统计方法方法、拟合方法、双窗口变步长搜寻法、选取阈值法得到三个不同处理阶段的4种不透水面指数相关系数、提取精度。6) Using mathematical statistics method, fitting method, double-window variable-step search method, and selection threshold method to obtain 4 kinds of impervious surface index correlation coefficients and extraction accuracy in three different processing stages.
进一步的，所述步骤1)研究区域的Landsat-8遥感影像是从专业网站购买或下载。Further, in the step 1) the Landsat-8 remote sensing image of the research area is purchased or downloaded from a professional website.
进一步的，所述步骤2)对原始遥感影像数据进行预处理，包括大气校正、辐射定标以及几何校正，具体包括：Further, the step 2) preprocesses the original remote sensing image data, including atmospheric correction, radiometric calibration and geometric correction, specifically including:
采用包括ENVI5.3在内的现有软件，在Landsat-8卫星影像的辅助下，对原始图像中包括热红外波段的所有波段进行几何精校正处理，再进行辐射定标，然后利用ENVI-FLASSH工具对各波段的地表反射率进行大气校正，得到经过大气校正后的地表反射率数据。Using the existing software including ENVI5.3, with the aid of Landsat-8 satellite imagery, all bands in the original image including thermal infrared band are geometrically finely corrected, then radiometrically calibrated, and then using ENVI-FLASSH The tool performs atmospheric correction on the surface reflectance of each band, and obtains the surface reflectance data after atmospheric correction.
进一步的，所述步骤3)获取辐射定标和FLASSH大气校正的遥感数据，具体包括：用公式Lλ＝gain·DN+offset进行辐射定标，Lλ表示定标后的表观反射率，gain为增益值；offset为偏移值，再进行FLASSH大气校正，FLASSH大气校正的基础是Modtran模型，而Modtran模型源自于大气辐射传输方程，计算公式为：
进一步的，所述步骤4)反演灰度值、辐射定标、大气校正三个不同处理阶段的归一化建筑指数NDBI、新型建筑用地指数IBI、城市指数UI、城市建成区指数BUAI4种不透水面指数，具体包括：Further, the step 4) inversion gray value, radiation calibration, atmospheric correction three different processing stages of normalized building index NDBI, new building land index IBI, urban index UI, urban built-up area index BUAI four different types. Pervious surface index, including:
BUAI＝NDBI-NDVIBUAI=NDBI-NDVI
Green为绿光波段，Red为红光波段，NIR为近红外波段，SWIR1为短波红外波段1，SWIR2为短波红外波段2，NDVI为归一化植被指数，对于Landsat-8影像而言，Blue、Green、Red、NIR、SWIR1、SWIR2分别对应波段TM2、TM 3、TM 4、TM 5、TM 6、TM 7。Green is the green band, Red is the red band, NIR is the near-infrared band, SWIR1 is the short-wave infrared band 1, SWIR2 is the short-wave infrared band 2, and NDVI is the normalized vegetation index. For Landsat-8 images, Blue, Green, Red, NIR, SWIR1, and SWIR2 correspond to the bands TM2, TM3, TM4, TM5, TM6, and TM7, respectively.
进一步的，所述步骤5)采用数理统计方法方法得到三个不同处理阶段的4种不透水面指数变化特征、分布范围，具体包括：Further, described step 5) adopts mathematical statistics method to obtain 4 kinds of impervious surface index variation characteristics and distribution ranges of three different treatment stages, specifically including:
(1)选取大量灰度值、辐射定标、大气校正三个不同处理阶段的NDBI、IBI、UI、BUAI不透水面指数样本点；(1) Select a large number of sample points of NDBI, IBI, UI, and BUAI impervious surface index in three different processing stages: gray value, radiometric calibration, and atmospheric correction;
(2)将样本点导入Excel统计变化特征；(2) Import the sample points into Excel statistical variation characteristics;
(3)将样本点导入Matlab统计分布范围。(3) Import the sample points into the Matlab statistical distribution range.
进一步的，所述步骤6)采用数理统计方法方法、拟合方法、双窗口变步长搜寻法、选取阈值法得到三个不同处理阶段的4种不透水面指数相关系数、提取精度，具体包括：Further, the step 6) adopts the mathematical statistics method, the fitting method, the double-window variable step-size search method, and the selection threshold method to obtain the correlation coefficients and extraction precisions of four kinds of impervious surface indices in three different processing stages, specifically including: :
(1)选取大量灰度值、辐射定标、大气校正三个不同处理阶段的NDBI、IBI、UI、BUAI不透水面指数样本点；(1) Select a large number of sample points of NDBI, IBI, UI, and BUAI impervious surface index in three different processing stages: gray value, radiometric calibration, and atmospheric correction;
(2)将样本点导入Matlab拟合相关系数，线性方程；(2) Import the sample points into Matlab to fit the correlation coefficient and linear equation;
(3)利用双窗口变步长搜寻法选取阈值法获取三个不同处理阶段每种指数的最佳阈值，最后对每种指数进行精度评价。(3) Using the double-window variable-step search method to select the threshold method to obtain the best threshold of each index in three different processing stages, and finally evaluate the accuracy of each index.
本发明的优点及有益效果如下：The advantages and beneficial effects of the present invention are as follows:
本发明以Landsat-8遥感分别在DN值、TOA反射率、Surface反射率下提取NDBI、IBI、UI，BUAI四种不透水面指数精度，并对在三种情况下的不透水面指数性能差异进行了综合评价。The present invention uses Landsat-8 remote sensing to extract NDBI, IBI, UI, and BUAI four kinds of impervious surface index precisions under DN value, TOA reflectivity, and Surface reflectivity, respectively, and analyzes the performance difference of impervious surface index under three conditions. A comprehensive evaluation was carried out.
NDBI、IBI、UI、BUAI在3种不同辐射水平下的直方图均发生了变化，在Surface反射率下的直方图区间范围变大，峰值和波谷值较大气校正前更为明显，直方图曲线更加的平滑，说明大气校正消除了大气，光照等因素对地物反射率的影响。NDBI、IBI、UI，BUAI的不透水面指数分布范围我们可以看出，在三种不同辐射水平下的最小值，最大值，均值，标准差的变化趋势的变化趋势基本相同。四个不透水面指数的最小值变小，最大值变大，取值范围逐渐增大，不透水面信息得到加强，大气校正后反演的不透水面指数的得到了改善。四个不透水面指数在Surface反射率下标准差最大，标准差越大，灰度级分布越分散，图像的目视效果越好，图像所含信息量越丰富，因此大气校正更有利于不透水面信息提取。在TOA反射率和Surface反射率下与DN值下的不透水面指数相互之间存在明显的线性相关性，又存在明显的区别。利用NDBI、IBI、UI、BUAI在DN值、TOA反射率、Surface反射率下提取不透水面物的精度有所差异，在Surface反射率下提取不透水面物的精度较高，NDBI、IBI、UI、BUAI在Surface反射率下的Overall Accuracy和Kappa系数相比DN值下的精度的有所提高，说明大气校正有助于提高不透水面信息提取的精度。。The histograms of NDBI, IBI, UI, and BUAI have all changed under the three different radiation levels. The histogram interval under the Surface reflectivity becomes larger, and the peak and trough values are larger than before. The histogram curve is more obvious. It is smoother, indicating that atmospheric correction eliminates the influence of atmospheric, light and other factors on the reflectivity of ground objects. From the distribution range of the impervious surface index of NDBI, IBI, UI, and BUAI, we can see that the change trends of the minimum, maximum, mean, and standard deviation of the three different radiation levels are basically the same. The minimum value of the four impervious surface indices becomes smaller, the maximum value becomes larger, the value range gradually increases, the impervious surface information is strengthened, and the inversion of the impervious surface index after atmospheric correction is improved. The standard deviation of the four impervious surface indices is the largest under the Surface reflectance. Permeable surface information extraction. There is an obvious linear correlation between the impervious surface index under the TOA reflectivity and the Surface reflectivity and the DN value, and there is an obvious difference. Using NDBI, IBI, UI, and BUAI to extract impervious surface objects under DN value, TOA reflectivity, and Surface reflectivity differs in accuracy. Compared with the DN value, the accuracy of UI and BUAI's Overall Accuracy and Kappa coefficient under the Surface reflectivity are improved, indicating that atmospheric correction helps to improve the accuracy of impervious surface information extraction. .
本文发明的创新点主要在(5)(6)步骤。目前大多数学者对于城市不透水面信息的提取，为了方便就直接使用原始影像的DN值反演，没有去考虑大气校正是否有助于提高不透水面指数性能。The innovations of the invention are mainly in steps (5) and (6). At present, most scholars directly use the DN value inversion of the original image for the convenience of extracting the information of the urban impervious surface, without considering whether the atmospheric correction can help to improve the performance of the impervious surface index.
(1)大气校正消除了大气，光照等因素对地物反射率的影响。(1) Atmospheric correction eliminates the influence of atmospheric, illumination and other factors on the reflectivity of ground objects.
(2)大气校正后标准差最大，标准差越大，灰度级分布越分散，图像的目视效果越好，图像所含信息量越丰富，因此大气校正更有利于建筑信息提取。(2) The standard deviation after atmospheric correction is the largest. The larger the standard deviation, the more scattered the gray level distribution, the better the visual effect of the image, and the richer the information contained in the image. Therefore, atmospheric correction is more conducive to the extraction of building information.
(3)在TOA反射率和Surface反射率下与DN值下的建筑指数相互之间存在明显的线性相关性，有时可以存在相互转换。(3) There is an obvious linear correlation between the TOA reflectivity and Surface reflectivity and the building index under the DN value, and sometimes there can be mutual conversion.
(4)NDBI指数、IBI指数、UI指数、BUAI指数在Surface反射率下的OverallAccuracy和Kappa系数相比DN值下的精度的有所提高，说明大气校正有助于提高建筑物提取的精度。(4) The accuracy of the NDBI index, IBI index, UI index, and BUAI index under the Surface reflectivity and Kappa coefficient are improved compared with those under the DN value, indicating that atmospheric correction helps to improve the accuracy of building extraction.
附图说明Description of drawings
图1是本发明提供优选实施例一种基于大气校正对不透水面指数性能差异影响的定量和定性描述的方法的流程图。FIG. 1 is a flow chart of a method for providing a quantitative and qualitative description of the impact of atmospheric correction on the difference in impervious surface index performance based on a preferred embodiment of the present invention.
具体实施方式Detailed ways
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、详细地描述。所描述的实施例仅仅是本发明的一部分实施例。The technical solutions in the embodiments of the present invention will be described clearly and in detail below with reference to the accompanying drawings in the embodiments of the present invention. The described embodiments are only some of the embodiments of the invention.
本发明解决上述技术问题的技术方案是：The technical scheme that the present invention solves the above-mentioned technical problems is:
以上所述步骤(1)研究区域的Landsat8遥感影像是从某些专业网站购买或下载。The Landsat8 remote sensing images of the research area in the above step (1) are purchased or downloaded from some professional websites.
进一步的，以上所述步骤(2)是借助包括ENVI5.3在内的现有软件，在Landsat-8卫星影像的辅助下，对原始图像中包括热红外波段的所有波段进行几何精校正处理，然后利用ENVI-FLASSH工具对各波段的地表反射率进行大气校正，得到经过大气校正后的地表反射率数据。Further, the above-mentioned step (2) is to use existing software including ENVI5.3, with the aid of Landsat-8 satellite images, to perform geometric fine-tuning processing on all bands in the original image including thermal infrared bands, Then use the ENVI-FLASSH tool to perform atmospheric correction on the surface reflectance of each band, and obtain the surface reflectance data after atmospheric correction.
进一步的，以上所述步骤(3)利用辐射定标和大气校正方法，步骤包括：用公式Lλ＝gain·DN+offset进行辐射定标，在进行FLASSH大气校正，FLASSH大气校正的基础是Modtran模型，而Modtran模型源自于大气辐射传输方程，因此其大气校正效果较好。计算公式为:
进一步的，以上所述步骤(4)反演了灰度值、辐射定标、大气校正三个不同处理阶段的NDBI、IBI、UI、BUAI 4种不透水面指数。Further, the above-mentioned step (4) inverts four impervious surface indices of NDBI, IBI, UI, and BUAI in three different processing stages: gray value, radiometric calibration, and atmospheric correction.
进一步的，以上所述步骤(5)反演4种不透水面这似乎具体包括：大气校正后影像的直方图两次峰值和波谷值较大气校正前更为明显，直方图曲线更加的平滑，有利于阈值的判定，依据统计特征来看，四种建筑指数在DN值、TOA反射率、Surface反射率下取值范围逐渐变大。在TOA反射率下反演不透水面指数均值最小，在Surface反射率下反演的不透水面指数标准差最大,最终得到大气校正对不透水面指数性能差异的影响。Further, the above-mentioned step (5) inversion of four kinds of impervious surfaces seems to specifically include: the two peaks and trough values of the histogram of the image after atmospheric correction are more obvious than those before atmospheric correction, and the histogram curve is smoother, It is beneficial to the determination of the threshold value. According to the statistical characteristics, the value ranges of the four building indices under the DN value, TOA reflectivity, and Surface reflectivity gradually become larger. The mean value of the inverted impervious surface index is the smallest under the TOA reflectivity, and the standard deviation of the inverted impervious surface index is the largest under the surface reflectivity. Finally, the effect of atmospheric correction on the performance difference of the impervious surface index is obtained.
进一步的，以上所述步骤(6)即利用步骤(5)建立的大气校正对不透水面指数性能差异的影响的分析，在TOA反射率和Surface反射率下的建筑指数数据与原始影像的建筑指数相互之间具有极强的正相关系数，又存在明显的区别，在DN值、TOA反射率、Surface反射率下的建筑指数的总体精度和Kappa值的的不相同，大气校正后的建筑指数总体精度和Kappa值相应提高了。Further, the above-mentioned step (6) is the analysis of the influence of the atmospheric correction established in step (5) on the performance difference of the impervious surface index, and the building index data under the TOA reflectivity and the surface reflectance The indices have a strong positive correlation coefficient with each other, and there are obvious differences. The overall accuracy of the building index under the DN value, TOA reflectivity, and Surface reflectivity is not the same as the Kappa value. After atmospheric correction, the building index Overall accuracy and Kappa values have been improved accordingly.
以上这些实施例应理解为仅用于说明本发明而不用于限制本发明的保护范围。在阅读了本发明的记载的内容之后，技术人员可以对本发明作各种改动或修改，这些等效变化和修饰同样落入本发明权利要求所限定的范围。The above embodiments should be understood as only for illustrating the present invention and not for limiting the protection scope of the present invention. After reading the contents of the description of the present invention, the skilled person can make various changes or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.
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